Influence of Hydraulic Resistance on the Osmotic Engine Model of Cell Migration

总结 了解细胞迁移的机制是细胞、发育和癌症研究中的一个基本问题 生物学几十年的研究表明，细胞迁移的分子基础是复杂的， 推动移徙的物理机制多种多样。我们已经证明，根据当地的 在微环境中，细胞迁移可以由肌动蛋白聚合以及渗透梯度驱动 细胞外的水通量。这种所谓的渗透引擎模型（OEM）在细胞紧密结合时非常突出。 密闭空间在体内，细胞在不同的微环境中迁移，从密集的3D细胞外 基质到组织中存在的狭窄微通道，到具有各种物理性质的复杂体细胞空间， 障碍.一个开放的和未解决的问题是什么是重要的变量，决定了相对 肌动蛋白聚合驱动和水基迁移机制在不同细胞中的作用 微环境最近的数据表明，细胞限制的程度和水力阻力 细胞所经历的变化代表了决定驱动细胞运动的机制的关键因素。理论 利用细胞质的两相模型的建模也预测了 细胞所经历的变化决定了水流/OEM对观察到的细胞速度的相对贡献。 越来越多的实验证据也表明，细胞可以感受到液压，并调节细胞的功能。 迁移机制在这项拨款申请中，我们建议开发一个综合建模和 描述肌动蛋白相和水相对细胞相对贡献的实验方法 迁移是外部水力阻力的函数。在目标1中，我们建议直接量化液压 通过在添加甲基纤维素的培养基中以2D检查细胞， 这增加了介质的粘度，并且在具有不同通道长度的限制性微通道内， 调节液压阻力。关键离子通道和转运蛋白的作用，参与建立 水通量和迁移的能量学将在实验和理论上进行探索。我们还将确定 负责感测液压阻力的关键机械敏感离子通道。在目标2中，我们将探索 肌动蛋白聚合，膜张力变化和OEM之间的相互作用，在环境升高 液压阻力我们还将扩展细胞迁移的两阶段理论模型， 膜张力和流动。由于细胞迁移速度可能取决于细胞形状，在目标3中，我们将开发 一个通用的两相移动边界方法来计算任意细胞形状的细胞运动。我们还将 探索OEM如何影响致密与多孔3D胶原基质中的细胞迁移， 不同的水力阻力。综合起来，我们将发现反直觉背后的机制 使用多学科方法观察在高液压阻力环境中的更快迁移， 包括最先进的微器件、成像、分子生物学工具以及数学建模沿着。

Summary Understanding the mechanisms of cell migration is a fundamental question in cell, developmental and cancer biology. Decades of research has shown that the molecular underpinnings of cell migration are complex and the physical mechanisms driving migration are diverse. We have shown that depending on the local microenvironment, cell migration can be driven by actin polymerization as well as an osmotic gradient-driven water flux external to the cell. This so-called osmotic engine model (OEM) is prominent when cells are in tightly confined spaces. In vivo, cells migrate within diverse microenvironments, ranging from dense 3D extracellular matrices to narrow microchannels present in tissue, to complex somatic spaces with various kinds of physical obstacles. An open and un-addressed question is what are the important variables that dictate the relative contribution of actin polymerization-driven and water-based migratory mechanisms in diverse microenvironments. Recent data reveal that the degree of cell confinement and the hydraulic resistance experienced by cells represent key factors in determining the mechanisms driving cell movement. Theoretical modeling utilizing a two-phase model of the cell cytoplasm also predicts that the hydraulic resistance experienced by the cell dictates the relative contribution of water flow/OEM to the observed cell speed. Mounting experimental evidence also suggests that cells can sense hydraulic pressure and modulate cell migration mechanisms. In this grant application, we propose to develop an integrated modeling and experimental approach to delineate the relative contributions of the actin-phase and the water-phase to cell migration as a function of external hydraulic resistance. In Aim 1, we propose to directly quantify how hydraulic resistance influences cell migration speeds by examining cells both in 2D in media with added methylcellulose, which increases medium viscosity, and inside confining microchannels of varying channel length, which also modulate hydraulic resistance. The roles of key ion channels and transporters that are involved in setting up water flux and the energetics of migration will be explored experimentally and theoretically. We will also identify the key mechanosensitive ion channels responsible for sensing hydraulic resistance. In Aim 2, we will explore the interplay between actin polymerization, membrane tension changes and OEM in environments of elevated hydraulic resistance. We will also extend the two-phase theoretical model of cell migration in include membrane tension and flows. Since cell migration speeds may depend on cell shape, in Aim 3, we will develop a general two-phase moving boundary method to compute cell movement for arbitrary cell shapes. We will also explore how OEM influences cell migration in dense vs more porous 3D collagen matrices, which exhibit different hydraulic resistances. Taken together, we will discover the mechanisms behind the counterintuitive observation of faster migration in high hydraulic resistance environments using a multidisciplinary approach, involving state-of-the-art microdevices, imaging, molecular biology tools along with mathematical modeling.